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Java Deep Learning Cookbook

You're reading from   Java Deep Learning Cookbook Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781788995207
Length 304 pages
Edition 1st Edition
Languages
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Author (1):
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Rahul Raj Rahul Raj
Author Profile Icon Rahul Raj
Rahul Raj
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Deep Learning in Java 2. Data Extraction, Transformation, and Loading FREE CHAPTER 3. Building Deep Neural Networks for Binary Classification 4. Building Convolutional Neural Networks 5. Implementing Natural Language Processing 6. Constructing an LSTM Network for Time Series 7. Constructing an LSTM Neural Network for Sequence Classification 8. Performing Anomaly Detection on Unsupervised Data 9. Using RL4J for Reinforcement Learning 10. Developing Applications in a Distributed Environment 11. Applying Transfer Learning to Network Models 12. Benchmarking and Neural Network Optimization 13. Other Books You May Enjoy

Technical requirements

You'll need the following to get the most out of this cookbook:

  • Java SE 7, or higher, installed
  • Basic core Java knowledge
  • DL4J basics
  • Maven basics
  • Basic data analytical skills
  • Deep learning/machine learning basics
  • OS command basics (Linux/Windows)
  • IntelliJ IDEA IDE (this is a very easy and hassle-free way of managing code; however, you're free to try another IDE, such as Eclipse)
  • Spring Boot basics (to integrate DL4J with Spring Boot for use with web applications)
We use DL4J version 1.0.0-beta3 throughout this book except for Chapter 7, Constructing an LSTM Neural Network for Sequence Classification, where we used the current latest version, 1.0.0-beta4, to avoid bugs.
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